Posted May 21, 2026
Develop robust, scalable Java/Python based backend systems that enable the orchestration of Agentic AI workflows. - Develop state-of-the-art AI/ML models for solving real-world data management challenges such as entity resolution, classification, similarity matching, and anomaly detection. - Integrate LLMs (e.g., OpenAI, Mistral, Claude, LLaMA) into backend pipelines to power autonomous or semi-autonomous decision-making. - Hands on experience with mobile front-end Flutter, React-native etc.
Develop scalable ML workflows using Spark, MLlib, PyTorch, TensorFlow, or MLFlow, with seamless integration into production systems. - Translate business needs into technical design and collaborate with data scientists, product managers, and platform engineers to operationalize models. - Work closely with various stakeholders to design agent architectures and LLM toolchains (using frameworks like LangGraph, Crew AI, AutoGen, etc.). - Implement services and APIs that manage prompt chaining, tool invocation, and contextual memory for agents. - Collaborate with data engineers to ensure clean, efficient, and real-time access to structured and semi-structured data. - prompt engineering best practices to improve agent behavior, task accuracy, and adaptability. - Monitor and optimize service performance, reliability, and scalability in production environments. - Continuously monitor and improve model performance using feedback loops, A/B testing, drift detection, and retraining strategies. - Contribute to code reviews, mentoring, and best practices for hybrid backend/AI development. ## Required Qualifications
5+ years of overall experience mobile front-end Flutter, React-native etc
2+ years of experience in developing and deploying machine learning models and AI products in production environments. - Experience in Agentic AI systems development using tools such as LangGraph, Crew AI, AutoGen, or similar. - Proficiency in Python (NumPy, scikit-learn, pandas, PyTorch/TensorFlow) and experience with large-scale data processing tools (Spark, Kafka, Airflow). - Experience integrating or orchestrating LLMs within business workflows or intelligent assistants. - Solid understanding of prompt engineering techniques (e.g., system messages, chaining, tool invocation prompts). - Familiarity with data engineering concepts, including pipelines, data models, and ETL workflows. - Strong grasp of object-oriented design, data structures, and algorithms. ## Preferred Qualifications
Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, RAG pipelines). - Background in building microservices or backend systems for data-rich AI/ML platforms. - Experience with vector databases, embedding services, or semantic search integration. - Knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and DevOps best practices. - Experience in developing LLM-powered agents, copilots, or task bots. ## What We Offer
Opportunity to work on cutting-edge backend and AI systems, including agentic automation and LLM innovation. - A flexible hybrid work model in our Bangalore office. - Competitive compensation with performance-based rewards. - A culture that promotes engineering excellence, experimentation, and growth.Access to learning platforms, technical workshops, and industry-leading AI research.
Don't want to apply yourself?
Our team writes your resume, applies for you, preps you for interviews, and negotiates your offer.
Browse Jobs
By Role
By City